I have a NumPy array
[None, None, None, None, 1, 2, None, 4, None]
The output I want is
[1, 2, None, 4, None]
I wrote this while loop but there is something wrong I guess
index = 0
while(numpyArray[index] is None):
numpyArray = np.delete(numpyArray, index)
index += 1
The output I am getting is
[None, None, 1, 2, None, 4, None]
The problem is that after you delete an item at position index, all subsequent indices will be shifted to the left by 1:
0 1 2 3
[a, b, c, d]
deleting at index == 1 will cause:
0 1 2
[a, c, d]
so that right after the deletion c and d have index -1 of what they had before the deletion.
The indexing is always contiguous.
So, in your code you first delete the item at position 0, all indexes gets shifted by -1 and when you advance the index, you are now considering not the second element (the one that originally was at index == 1) but the the third element (the one that originally was at index == 2), etc.
If you leave out the index += 1 line, the code should work.
Finally, please note that NumPy arrays are not particularly efficient at resizing. Python lists are generally faster at resizing.
You shouldn't delete elements from a list (or, as it happens, numpy.array) while iterating over it. Instead, create a copy:
import itertools
newArray = np.array(list(itertools.dropwhile(lambda x: x is None, numpyArray)))
for item in items: ...This is not the correct way to do this in python, try use one of the following
numpyArray = [i for i in numpyArray if i is not None]
or
numpyArray = np.array(list(filter(lambda i: i is not None, numpyArray)))
Nones, not just leading ones.